期刊文献+

基于背景间运算的部分已知概念构造

Construction of partially-known formal concepts basedon operations of formal contexts
下载PDF
导出
摘要 概念是利用形式概念分析进行知识获取的基础。在不完备形式背景中,为了表达“一定具有”以及“可能具有”的关系,概念的外延或内涵通常以区间集的形式表达,称这样的概念为部分已知概念。由部分已知概念的定义可知,其本质与不完备背景的最小和最大完备化有关,因而考虑对最小和最大完备化背景进行运算来寻找部分已知概念。通过将不完备形式背景的最小完备化与最大完备化分别进行并置和叠置构造两个新背景,其概念格分别同构于SE-ISI概念格和ISE-SI概念格,从而提出了构建SE-ISI概念格和ISE-SI概念格的新方法。对于ISE-ISI概念,使用不完备形式背景的最小与最大完备化的直和运算构造了新的形式背景,基于此背景提出了寻找ISE-ISI概念的方法。 Concepts are the foundation for knowledge acquisition through formal concept analysis.In incomplete formal contexts,in order to express“jointly must possessing(possessed)”and“jointly might possessing(possessed)”relationships,the extent or intent of concepts is usually expressed in the form of interval set.We refer to such concepts as partially-known formal concepts.From the definition of partially-known formal concepts,it can be seen that their essence is related to the least and greatest completions of incomplete formal contexts.Therefore,we consider performing operations on the least and greatest completions of incomplete formal contexts to find partially-known formal concepts.We construct two new formal contexts based on the apposition and subposition of the least and greatest completions.Their concept lattices are isomorphic to the SE-ISI concept lattice and the ISE-SI concept lattice,respectively.Therefore,the new methods for constructing SE-ISI concept lattice and ISE-SI concept lattice are proposed.For the ISE-ISI concept,we use direct sum operation of the least and greatest completions to construct a new formal context,and propose a method to search for the ISE-ISI concepts.
作者 田雪 任睿思 TIAN Xue;REN Ruisi(School of Mathematics,Northwest University,Xi’an 710127,China;Institute of Concepts,Cognition and Intelligence,Northwest University,Xi’an 710127,China)
出处 《西北大学学报(自然科学版)》 CAS CSCD 北大核心 2024年第2期209-219,共11页 Journal of Northwest University(Natural Science Edition)
基金 国家自然科学基金(62006190)。
关键词 不完备形式背景 部分已知概念 并置 叠置 直和 incomplete formal context partially-known formal concept apposition subposition direct sum
  • 相关文献

参考文献1

二级参考文献18

  • 1Oosthuizen G D. The Application of Concept Lattice to Machine Learning. Technical Report, University of Pretoria, South Africa, 1996.
  • 2Ho T B. Incremental conceptual clustering in the framework of Galois lattice. In: Lu H, Motoda H, Liu H, eds. KDD: Techniques and Applications. Singapore: World Scientific, 1997. 49~64.
  • 3Kent R E. Bowman C M. Digital Libraries, Conceptual Knowledge Systems and the Nebula Interface. Technical Report, University of Arkansas, 1995.
  • 4Corbett D, Burrow A L. Knowledge reuse in SEED exploiting conceptual graphs. In: International Conference on Conceptual Graphs (ICCS'96). Sydney, 1996. University of New South Wales, 1996. 56~60.
  • 5Schmitt I, Saake G. Merging Inheritance hierarchies for scheme integration based on concept lattices [EB/OL]. http: //www.mathematic.tu-darm stadt.de/ags/ag1.
  • 6Siff M, Reps T. Identifying modules via concept analysis. In: Harrold M J, Visaggio G, eds. International conference on software maintenance. Bari, Italy. Washington, DC: IEEE Computer Society, 1997. 170~179.
  • 7Ho T B. An approach to concept formation based on formal concept analysis. IEICE Trans Information and Systems, 1995, E782D (5): 553~559.
  • 8Carpineto C, Romano G. Galois: an order-theoretic approach to conceptual clustering. In: Utgoff P, ed. Proceedings of ICML 293. Amherst: Elsevier, 1993. 33~40.
  • 9Godin R. Incremental concept formation algorithm based on Galois (concept) lattices. Computational Intelligence, 1995, 11(2): 246~267.
  • 10Yao Y Y. Concept lattices in rough set theory. In: Dick S, Kurgan L, Pedrycz W, eds. Proceedings of 2004 Annual Meeting of the North American Fuzzy Information Processing Society (NAFIPS 2004), IEEE Catalog Number: 04TH8736, 2004, June 27~30. 796~801.

共引文献192

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部